1. Statement of the Technical Field
The present invention relates to the field of systems administration and more particularly to the administration of an autonomic system.
2. Description of the Related Art
In the famed manifesto Paul Horn, Autonomic Computing: IBM's Perspective on the State of Information Technology, (IBM Corporation 2001)(hereinafter, the “Manifesto”), Paul Horn, Senior Vice President of IBM Research, observed, “It's not about keeping pace with Moore's Law, but rather dealing with the consequences of its decades-long reign.” Given this observation, Horn suggested a computing parallel to the autonomic nervous system of the biological sciences. Namely, whereas the autonomic nervous system of a human being monitors, regulates, repairs and responds to changing conditions without any conscious effort on the part of the human being, in an autonomic computing system, the system must self-regulate, self-repair and respond to changing conditions, without requiring any conscious effort on the part of the computing system operator.
Thus, while the autonomic nervous system can relieve the human being from the burden of coping with complexity, so too can an autonomic computing system. Rather, the computing system itself can bear the responsibility of coping with its own complexity. The crux of the Manifesto relates to eight principal characteristics of an autonomic computing system:                I. The system must “know itself” and include those system components which also possess a system identify.        II. The system must be able to configure and reconfigure itself under varying and unpredictable conditions.        III. The system must never settle for the status quo and the system must always look for ways to optimize its workings.        IV. The system must be self-healing and capable of recovering from routine and extraordinary events that might cause some of its parts to malfunction.        V. The system must be an expert in self-protection.        VI. The system must know its environment and the context surrounding its activity, and act accordingly.        VII. The system must adhere to open standards.        VIII. The system must anticipate the optimized resources needed while keeping its complexity hidden from the user.        
Importantly, in accordance with the eight tenants of autonomic computing, several single system and peer-to-peer systems have been proposed in which self-configuration, management and healing have provided a foundation for autonomic operation. Self-managing systems which comport with the principles of autonomic computing reduce the cost of owning and operating computing systems. Yet, implementing a purely autonomic system has proven revolutionary. Rather, as best expressed in the IBM Corporation white paper, Autonomic Computing Concepts (IBM Corporation 2001)(hereinafter, the “IBM White Paper”), “Delivering system wide autonomic environments is an evolutionary process enabled by technology, but it is ultimately implemented by each enterprise through the adoption of these technologies and supporting processes.”
In the IBM White Paper, five levels have been logically identified for the path to autonomic computing. These five levels range from the most basic, manual process to the most purely autonomic. In further illustration, FIG. 1 is a block illustration of the five levels of the path to autonomic computing. The Basic Level 110 represents a starting point of information technology environments. Each infrastructure element can be managed independently by an administrator who can establish, configure, monitor and ultimately replace the element. At the Managed Level 120, systems management technologies can be used to collect information from disparate systems onto fewer consoles, reducing the time consumed for the administrator to collect and synthesize information as the environment becomes more complex.
Notably, the Predictive Level 130 incorporates new technologies to provide a correlation among several infrastructure elements. These infrastructure elements can begin to recognize patterns, predict the optimal configuration of the system, and provide advice as to the nature of the course of action which the administrator ought to take. By comparison, at the Adaptive Level 140 the system itself can automatically perform appropriate actions responsive to the information collected by the system and the knowledge of the state of the system. Finally, at the Autonomic Level 150 the entire information technology infrastructure operation is governed by business policies and objectives. Users interact with the autonomic technology only to monitor the business processes, alter the objects, or both.
Between each of the levels 110, 120, 130, 140, 150 of computing management, thresholds 105, 115, 125, 135 exist. The transition from the Basic Level 110 through to the Autonomic Level 150 necessarily crosses each threshold 105, 115, 125, 135 as the management principles vary from manual characteristics 170 through to autonomic characteristics 180. Yet, the mechanism for automatically transitioning from one level to the next has not been defined. In fact, often the level corresponding to a management configuration often is fixed from the start and cannot be varied without substantial human intervention and reconfiguration. Certainly, the determination of when to transition from the Predictive Level 130 to the Adaptive Level 140 has not been defined. Nevertheless, it will be apparent to the skilled artisan that the primary difference between the Predictive Level 130 and the Adaptive Level is one of trust in the system's ability to manage its responsible elements without human intervention.